满足条件时用其他行的总和替换行值
Replace a row value with sum of other rows when conditions are met
我正在尝试找出如何根据多个条件对行求和，但保留我的数据框中的所有行，因此只有满足条件的行具有求和值，所有其他具有原始值（来自列称为 iresult_posPPP）。我有多个国家、不同年份、分区等的数据。我的 ISO 列是 'ALL' 我需要这个值是 iresult_posPPP 中所有行的总和，这些行对 DataYear 具有相同的值，除法、FurtherDetails1 和 FurtherDetails2。
我在下面附上了我的数据框的输出：
Data <- structure(list(ID.x = c(NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA), Indicator = c("Gym and Leisure Centre",
"Gym and Leisure Centre", "Gym and Leisure Centre", "Gym and Leisure Centre",
"Gym and Leisure Centre", "Gym and Leisure Centre", "Gym and Leisure Centre",
"Gym and Leisure Centre", "Gym and Leisure Centre", "Gym and Leisure Centre",
"Gym and Leisure Centre", "Gym and Leisure Centre", "Gym and Leisure Centre",
"Gym and Leisure Centre", "Gym and Leisure Centre", "Gym and Leisure Centre",
"Gym and Leisure Centre", "Gym and Leisure Centre", "Gym and Leisure Centre",
"Gym and Leisure Centre", "Gym and Leisure Centre"), IndicatorID = c(98L,
98L, 98L, 98L, 98L, 98L, 98L, 98L, 98L, 98L, 98L, 98L, 98L, 98L,
98L, 98L, 98L, 98L, 98L, 98L, 98L), InputA = c(3762.134507, 4447.309316,
4293.110921, 3862.76676, 4071.175351, 4323.016371, 4036.130293,
4450.854575, 4224.807119, 4563, 4888.173223, 4473.037451, 4136.032594,
4429.615323, 4972.768468, 4910.636192, 4947.585664, 4119.657378,
4809.477176, 4135.606089, 4935.381334), InputAName = c("Total number of people using the gym",
"Total number of people using the gym", "Total number of people using the gym",
"Total number of people using the gym", "Total number of people using the gym",
"Total number of people using the gym", "Total number of people using the gym",
"Total number of people using the gym", "Total number of people using the gym",
"Total number of people using the gym", "Total number of people using the gym",
"Total number of people using the gym", "Total number of people using the gym",
"Total number of people using the gym", "Total number of people using the gym",
"Total number of people using the gym", "Total number of people using the gym",
"Total number of people using the gym", "Total number of people using the gym",
"Total number of people using the gym", "Total number of people using the gym"
), InputAUnit = c("#", "#", "#", "#", "#", "#", "#", "#", "#",
"#", "#", "#", "#", "#", "#", "#", "#", "#", "#", "#", "#"),
OutputCode = c("GBP", "GBP", "GBP", "GBP", "GBP", "GBP",
"GBP", "GBP", "GBP", "GBP", "GBP", "GBP", "GBP", "GBP", "GBP",
"GBP", "GBP", "GBP", "GBP", "GBP", "GBP"), DataYear = c(2016L,
2016L, 2016L, 2016L, 2016L, 2016L, 2016L, 2016L, 2016L, 2017L,
2017L, 2017L, 2017L, 2017L, 2017L, 2017L, 2017L, 2017L, 2017L,
2017L, 2017L), Country.x = c("Uzbekistan", "Vanuatu", "Venezuela, RB",
"Vietnam", "Virgin Islands (U.S.)", "West Bank and Gaza",
"Yemen, Rep.", "Zambia", "Zimbabwe", "ALL", "Afghanistan",
"Albania", "Algeria", "American Samoa", "Andorra", "Angola",
"Antigua and Barbuda", "Argentina", "Armenia", "Aruba", "Australia"
), ISO = c("UZB", "VUT", "VEN", "VNM", "VIR", "PSE", "YEM",
"ZMB", "ZWE", "ALL", "AFG", "ALB", "DZA", "ASM", "AND", "AGO",
"ATG", "ARG", "ARM", "ABW", "AUS"), Division = c("Two", "Two",
"Two", "Two", "Two", "Two", "Two", "Two", "Two", "One", "One",
"One", "One", "One", "One", "One", "One", "One", "One", "One",
"One"), FurtherDetails1 = c("fd1b", "fd1b", "fd1b", "fd1b",
"fd1b", "fd1b", "fd1b", "fd1b", "fd1b", "fd1a", "fd1a", "fd1a",
"fd1a", "fd1a", "fd1a", "fd1a", "fd1a", "fd1a", "fd1a", "fd1a",
"fd1a"), FurtherDetails2 = c("fd2b", "fd2b", "fd2b", "fd2b",
"fd2b", "fd2b", "fd2b", "fd2b", "fd2b", "fd2a", "fd2a", "fd2a",
"fd2a", "fd2a", "fd2a", "fd2a", "fd2a", "fd2a", "fd2a", "fd2a",
"fd2a"), ID.y = c(168L, 168L, 168L, 168L, 168L, 168L, 168L,
168L, 168L, 189L, 189L, 189L, 189L, 189L, 189L, 189L, 189L,
189L, 189L, 189L, 189L), Code.x = c("GBP", "GBP", "GBP",
"GBP", "GBP", "GBP", "GBP", "GBP", "GBP", "GBP", "GBP", "GBP",
"GBP", "GBP", "GBP", "GBP", "GBP", "GBP", "GBP", "GBP", "GBP"
), CoefficientYear = c(2017L, 2017L, 2017L, 2017L, 2017L,
2017L, 2017L, 2017L, 2017L, 2017L, 2017L, 2017L, 2017L, 2017L,
2017L, 2017L, 2017L, 2017L, 2017L, 2017L, 2017L), Percent = c(-2.69,
-2.69, -2.69, -2.69, -2.69, -2.69, -2.69, -2.69, -2.69, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0), CoeffqInflation = c(-0.0269,
-0.0269, -0.0269, -0.0269, -0.0269, -0.0269, -0.0269, -0.0269,
-0.0269, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0), Method = c("",
"", "", "", "", "", "", "", "", "", "", "", "", "", "", "",
"", "", "", "", ""), ID.x.x = c(248L, 248L, 248L, 248L, 248L,
248L, 248L, 248L, 248L, 248L, 248L, 248L, 248L, 248L, 248L,
248L, 248L, 248L, 248L, 248L, 248L), InputCode = c("GBP",
"GBP", "GBP", "GBP", "GBP", "GBP", "GBP", "GBP", "GBP", "GBP",
"GBP", "GBP", "GBP", "GBP", "GBP", "GBP", "GBP", "GBP", "GBP",
"GBP", "GBP"), CoeffqFactor = c(1, 1, 1, 1, 1, 1, 1, 1, 1,
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1), Year = c(2017L, 2017L,
2017L, 2017L, 2017L, 2017L, 2017L, 2017L, 2017L, 2017L, 2017L,
2017L, 2017L, 2017L, 2017L, 2017L, 2017L, 2017L, 2017L, 2017L,
2017L), Type = c(NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA), ID.y.y = c(212L,
213L, 214L, 215L, 216L, 217L, 218L, 219L, 220L, 221L, 1L,
2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L), Country.y = c("Uzbekistan",
"Vanuatu", "Venezuela, RB", "Vietnam", "Virgin Islands (U.S.)",
"West Bank and Gaza", "Yemen, Rep.", "Zambia", "Zimbabwe",
"ALL", "Afghanistan", "Albania", "Algeria", "American Samoa",
"Andorra", "Angola", "Antigua and Barbuda", "Argentina",
"Armenia", "Aruba", "Australia"), Currency = c("GBP", "GBP",
"GBP", "GBP", "GBP", "GBP", "GBP", "GBP", "GBP", "GBP", "GBP",
"GBP", "GBP", "GBP", "GBP", "GBP", "GBP", "GBP", "GBP", "GBP",
"GBP"), CoeffqPPP = c(0.184436278, 0.184436278, 0.367527677,
0.184436278, 0.994525717, 0.184436278, 0.184436278, 0.184436278,
0.112411792, 0, 0.112411792, 0.347344672, 0.367527677, 0.367527677,
0.994525717, 0.264750217, 0.994525717, 0.389806873, 0.188019865,
0.994525717, 0.994525717), Step = c(3, 3, 3, 3, 3, 3, 3,
3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3), Coeffq = c(2756.10980649717,
2756.10980649717, 2756.10980649717, 2756.10980649717, 2756.10980649717,
2756.10980649717, 2756.10980649717, 2756.10980649717, 2756.10980649717,
2756.10980649717, 2756.10980649717, 2756.10980649717, 2756.10980649717,
2756.10980649717, 2756.10980649717, 2756.10980649717, 2756.10980649717,
2756.10980649717, 2756.10980649717, 2756.10980649717, 2756.10980649717
), CoeffqYear = c("2017", "2017", "2017", "2017", "2017",
"2017", "2017", "2017", "2017", "2017", "2017", "2017", "2017",
"2017", "2017", "2017", "2017", "2017", "2017", "2017", "2017"
), CoeffqUnit = c("GBP", "GBP", "GBP", "GBP", "GBP", "GBP",
"GBP", "GBP", "GBP", "GBP", "GBP", "GBP", "GBP", "GBP", "GBP",
"GBP", "GBP", "GBP", "GBP", "GBP", "GBP"), Step2iresult = c(1.32904727554592,
1.57109861939866, 1.51662503362256, 1.36459757855418, 1.43822197171544,
1.52718971619107, 1.42584162253612, 1.57235105117809, 1.49249538546973,
1.61196860639412, 1.72684237959508, 1.58018758409756, 1.46113405578585,
1.56484787181204, 1.75672729723484, 1.73477786082112, 1.74783098133106,
1.45534919185534, 1.69904146852532, 1.46098338458917, 1.74351956410071
), iresult_pos = c(3564.46552325877, 4213.64007550875, 4067.54352800449,
3659.81038551155, 3857.2688325682, 4095.8776944954, 3824.06510187511,
4216.9990605352, 4002.82852462449, 4442.76248384841, 4759.36721667692,
4355.17049663636, 4027.04589975837, 4312.8925651774, 4841.73333125022,
4781.23827430327, 4817.21410774609, 4011.10217955023, 4682.744853048,
4026.63063339563, 4805.33136843763), iresult_posPPP = c(675.590128629298,
798.631273618818, 1536.26022396863, 693.661294511865, 3942.19818248036,
776.311208628047, 724.793273270513, 799.267918050159, 462.403789458181,
0, 535.008997612704, 1512.74526765823, 1480.05082471057,
1585.10738563022, 4815.22831278442, 1265.8338706505, 4790.8433144487,
1563.55519789396, 880.449055099529, 4004.58771777195, 4779.02562461803
), iresult_pos_m = c(0.00356446552325877, 0.00421364007550875,
0.00406754352800449, 0.00365981038551155, 0.0038572688325682,
0.0040958776944954, 0.00382406510187511, 0.0042169990605352,
0.00400282852462449, 0.00444276248384841, 0.00475936721667692,
0.00435517049663636, 0.00402704589975837, 0.0043128925651774,
0.00484173333125022, 0.00478123827430327, 0.00481721410774609,
0.00401110217955023, 0.004682744853048, 0.00402663063339563,
0.00480533136843763), ID = c(NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA),
StepName = c("Avoided cost of Dementia", "Avoided cost of Dementia",
"Avoided cost of Dementia", "Avoided cost of Dementia", "Avoided cost of Dementia",
"Avoided cost of Dementia", "Avoided cost of Dementia", "Avoided cost of Dementia",
"Avoided cost of Dementia", "Avoided cost of Dementia", "Avoided cost of Dementia",
"Avoided cost of Dementia", "Avoided cost of Dementia", "Avoided cost of Dementia",
"Avoided cost of Dementia", "Avoided cost of Dementia", "Avoided cost of Dementia",
"Avoided cost of Dementia", "Avoided cost of Dementia", "Avoided cost of Dementia",
"Avoided cost of Dementia"), ImpactID = c(10L, 10L, 10L,
10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L,
10L, 10L, 10L, 10L, 10L, 10L), Allocation = c(1, 1, 1, 1,
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1), Polarity = c("Positive",
"Positive", "Positive", "Positive", "Positive", "Positive",
"Positive", "Positive", "Positive", "Positive", "Positive",
"Positive", "Positive", "Positive", "Positive", "Positive",
"Positive", "Positive", "Positive", "Positive", "Positive"
), Waterfall = c("Yes", "Yes", "Yes", "Yes", "Yes", "Yes",
"Yes", "Yes", "Yes", "Yes", "Yes", "Yes", "Yes", "Yes", "Yes",
"Yes", "Yes", "Yes", "Yes", "Yes", "Yes"), Int_Ext = c("External",
"External", "External", "External", "External", "External",
"External", "External", "External", "External", "External",
"External", "External", "External", "External", "External",
"External", "External", "External", "External", "External"
), ImpactCode = c("GDF", "GDF", "GDF", "GDF", "GDF", "GDF",
"GDF", "GDF", "GDF", "GDF", "GDF", "GDF", "GDF", "GDF", "GDF",
"GDF", "GDF", "GDF", "GDF", "GDF", "GDF"), ImpactName = c("Government // Direct Financial",
"Government // Direct Financial", "Government // Direct Financial",
"Government // Direct Financial", "Government // Direct Financial",
"Government // Direct Financial", "Government // Direct Financial",
"Government // Direct Financial", "Government // Direct Financial",
"Government // Direct Financial", "Government // Direct Financial",
"Government // Direct Financial", "Government // Direct Financial",
"Government // Direct Financial", "Government // Direct Financial",
"Government // Direct Financial", "Government // Direct Financial",
"Government // Direct Financial", "Government // Direct Financial",
"Government // Direct Financial", "Government // Direct Financial"
), Name = c("Gym and Leisure Centres", "Gym and Leisure Centres",
"Gym and Leisure Centres", "Gym and Leisure Centres", "Gym and Leisure Centres",
"Gym and Leisure Centres", "Gym and Leisure Centres", "Gym and Leisure Centres",
"Gym and Leisure Centres", "Gym and Leisure Centres", "Gym and Leisure Centres",
"Gym and Leisure Centres", "Gym and Leisure Centres", "Gym and Leisure Centres",
"Gym and Leisure Centres", "Gym and Leisure Centres", "Gym and Leisure Centres",
"Gym and Leisure Centres", "Gym and Leisure Centres", "Gym and Leisure Centres",
"Gym and Leisure Centres"), Capital = c("Manufactured", "Manufactured",
"Manufactured", "Manufactured", "Manufactured", "Manufactured",
"Manufactured", "Manufactured", "Manufactured", "Manufactured",
"Manufactured", "Manufactured", "Manufactured", "Manufactured",
"Manufactured", "Manufactured", "Manufactured", "Manufactured",
"Manufactured", "Manufactured", "Manufactured"), Flow = c("TBC",
"TBC", "TBC", "TBC", "TBC", "TBC", "TBC", "TBC", "TBC", "TBC",
"TBC", "TBC", "TBC", "TBC", "TBC", "TBC", "TBC", "TBC", "TBC",
"TBC", "TBC"), iresult = c(3564.46552325877, 4213.64007550875,
4067.54352800449, 3659.81038551155, 3857.2688325682, 4095.8776944954,
3824.06510187511, 4216.9990605352, 4002.82852462449, 4442.76248384841,
4759.36721667692, 4355.17049663636, 4027.04589975837, 4312.8925651774,
4841.73333125022, 4781.23827430327, 4817.21410774609, 4011.10217955023,
4682.744853048, 4026.63063339563, 4805.33136843763), iresult_m = c(0.00356446552325877,
0.00421364007550875, 0.00406754352800449, 0.00365981038551155,
0.0038572688325682, 0.0040958776944954, 0.00382406510187511,
0.0042169990605352, 0.00400282852462449, 0.00444276248384841,
0.00475936721667692, 0.00435517049663636, 0.00402704589975837,
0.0043128925651774, 0.00484173333125022, 0.00478123827430327,
0.00481721410774609, 0.00401110217955023, 0.004682744853048,
0.00402663063339563, 0.00480533136843763)), row.names = 1760:1780, class = "data.frame")
这是我目前正在尝试获得的代码要点 运行，目前正在考虑 if 语句方法：
Data %>%
mutate(iresult_pos = ifelse(ISO= 'ALL', (sum of the rows in iresult_posPPP where DataYear, Division, FurtherDetails1 and FutherDetails2 are the same), iresult_posPPP)
有没有一种简洁的方法可以做到这一点，或者我可能遗漏了一个步骤，因为我一直在绞尽脑汁/绕过堆栈溢出线程，想不出一个好的方法来做到这一点。任何帮助将不胜感激！
谢谢！
可能我们需要按总和分组
library(dplyr)
Data %>%
group_by(DataYear, Division, FurtherDetails1, FurtherDetails2) %>%
mutate(iresult_pos =sum(iresult_posPPP))
另一个选项，使用虚拟数据集来展示它是如何工作的：
# create dummy data
data <- data.frame(replicate(10,sample(0:1,1000,rep=TRUE)))
# sum X2, X3, X4, X9 where X1 == 1, store as X11
data <- data %>% mutate(
X11 = rowSums(select_(.,'X2','X3','X4','X9')))
我正在尝试找出如何根据多个条件对行求和，但保留我的数据框中的所有行，因此只有满足条件的行具有求和值，所有其他具有原始值（来自列称为 iresult_posPPP）。我有多个国家、不同年份、分区等的数据。我的 ISO 列是 'ALL' 我需要这个值是 iresult_posPPP 中所有行的总和，这些行对 DataYear 具有相同的值，除法、FurtherDetails1 和 FurtherDetails2。
我在下面附上了我的数据框的输出：
Data <- structure(list(ID.x = c(NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA), Indicator = c("Gym and Leisure Centre",
"Gym and Leisure Centre", "Gym and Leisure Centre", "Gym and Leisure Centre",
"Gym and Leisure Centre", "Gym and Leisure Centre", "Gym and Leisure Centre",
"Gym and Leisure Centre", "Gym and Leisure Centre", "Gym and Leisure Centre",
"Gym and Leisure Centre", "Gym and Leisure Centre", "Gym and Leisure Centre",
"Gym and Leisure Centre", "Gym and Leisure Centre", "Gym and Leisure Centre",
"Gym and Leisure Centre", "Gym and Leisure Centre", "Gym and Leisure Centre",
"Gym and Leisure Centre", "Gym and Leisure Centre"), IndicatorID = c(98L,
98L, 98L, 98L, 98L, 98L, 98L, 98L, 98L, 98L, 98L, 98L, 98L, 98L,
98L, 98L, 98L, 98L, 98L, 98L, 98L), InputA = c(3762.134507, 4447.309316,
4293.110921, 3862.76676, 4071.175351, 4323.016371, 4036.130293,
4450.854575, 4224.807119, 4563, 4888.173223, 4473.037451, 4136.032594,
4429.615323, 4972.768468, 4910.636192, 4947.585664, 4119.657378,
4809.477176, 4135.606089, 4935.381334), InputAName = c("Total number of people using the gym",
"Total number of people using the gym", "Total number of people using the gym",
"Total number of people using the gym", "Total number of people using the gym",
"Total number of people using the gym", "Total number of people using the gym",
"Total number of people using the gym", "Total number of people using the gym",
"Total number of people using the gym", "Total number of people using the gym",
"Total number of people using the gym", "Total number of people using the gym",
"Total number of people using the gym", "Total number of people using the gym",
"Total number of people using the gym", "Total number of people using the gym",
"Total number of people using the gym", "Total number of people using the gym",
"Total number of people using the gym", "Total number of people using the gym"
), InputAUnit = c("#", "#", "#", "#", "#", "#", "#", "#", "#",
"#", "#", "#", "#", "#", "#", "#", "#", "#", "#", "#", "#"),
OutputCode = c("GBP", "GBP", "GBP", "GBP", "GBP", "GBP",
"GBP", "GBP", "GBP", "GBP", "GBP", "GBP", "GBP", "GBP", "GBP",
"GBP", "GBP", "GBP", "GBP", "GBP", "GBP"), DataYear = c(2016L,
2016L, 2016L, 2016L, 2016L, 2016L, 2016L, 2016L, 2016L, 2017L,
2017L, 2017L, 2017L, 2017L, 2017L, 2017L, 2017L, 2017L, 2017L,
2017L, 2017L), Country.x = c("Uzbekistan", "Vanuatu", "Venezuela, RB",
"Vietnam", "Virgin Islands (U.S.)", "West Bank and Gaza",
"Yemen, Rep.", "Zambia", "Zimbabwe", "ALL", "Afghanistan",
"Albania", "Algeria", "American Samoa", "Andorra", "Angola",
"Antigua and Barbuda", "Argentina", "Armenia", "Aruba", "Australia"
), ISO = c("UZB", "VUT", "VEN", "VNM", "VIR", "PSE", "YEM",
"ZMB", "ZWE", "ALL", "AFG", "ALB", "DZA", "ASM", "AND", "AGO",
"ATG", "ARG", "ARM", "ABW", "AUS"), Division = c("Two", "Two",
"Two", "Two", "Two", "Two", "Two", "Two", "Two", "One", "One",
"One", "One", "One", "One", "One", "One", "One", "One", "One",
"One"), FurtherDetails1 = c("fd1b", "fd1b", "fd1b", "fd1b",
"fd1b", "fd1b", "fd1b", "fd1b", "fd1b", "fd1a", "fd1a", "fd1a",
"fd1a", "fd1a", "fd1a", "fd1a", "fd1a", "fd1a", "fd1a", "fd1a",
"fd1a"), FurtherDetails2 = c("fd2b", "fd2b", "fd2b", "fd2b",
"fd2b", "fd2b", "fd2b", "fd2b", "fd2b", "fd2a", "fd2a", "fd2a",
"fd2a", "fd2a", "fd2a", "fd2a", "fd2a", "fd2a", "fd2a", "fd2a",
"fd2a"), ID.y = c(168L, 168L, 168L, 168L, 168L, 168L, 168L,
168L, 168L, 189L, 189L, 189L, 189L, 189L, 189L, 189L, 189L,
189L, 189L, 189L, 189L), Code.x = c("GBP", "GBP", "GBP",
"GBP", "GBP", "GBP", "GBP", "GBP", "GBP", "GBP", "GBP", "GBP",
"GBP", "GBP", "GBP", "GBP", "GBP", "GBP", "GBP", "GBP", "GBP"
), CoefficientYear = c(2017L, 2017L, 2017L, 2017L, 2017L,
2017L, 2017L, 2017L, 2017L, 2017L, 2017L, 2017L, 2017L, 2017L,
2017L, 2017L, 2017L, 2017L, 2017L, 2017L, 2017L), Percent = c(-2.69,
-2.69, -2.69, -2.69, -2.69, -2.69, -2.69, -2.69, -2.69, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0), CoeffqInflation = c(-0.0269,
-0.0269, -0.0269, -0.0269, -0.0269, -0.0269, -0.0269, -0.0269,
-0.0269, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0), Method = c("",
"", "", "", "", "", "", "", "", "", "", "", "", "", "", "",
"", "", "", "", ""), ID.x.x = c(248L, 248L, 248L, 248L, 248L,
248L, 248L, 248L, 248L, 248L, 248L, 248L, 248L, 248L, 248L,
248L, 248L, 248L, 248L, 248L, 248L), InputCode = c("GBP",
"GBP", "GBP", "GBP", "GBP", "GBP", "GBP", "GBP", "GBP", "GBP",
"GBP", "GBP", "GBP", "GBP", "GBP", "GBP", "GBP", "GBP", "GBP",
"GBP", "GBP"), CoeffqFactor = c(1, 1, 1, 1, 1, 1, 1, 1, 1,
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1), Year = c(2017L, 2017L,
2017L, 2017L, 2017L, 2017L, 2017L, 2017L, 2017L, 2017L, 2017L,
2017L, 2017L, 2017L, 2017L, 2017L, 2017L, 2017L, 2017L, 2017L,
2017L), Type = c(NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA), ID.y.y = c(212L,
213L, 214L, 215L, 216L, 217L, 218L, 219L, 220L, 221L, 1L,
2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L), Country.y = c("Uzbekistan",
"Vanuatu", "Venezuela, RB", "Vietnam", "Virgin Islands (U.S.)",
"West Bank and Gaza", "Yemen, Rep.", "Zambia", "Zimbabwe",
"ALL", "Afghanistan", "Albania", "Algeria", "American Samoa",
"Andorra", "Angola", "Antigua and Barbuda", "Argentina",
"Armenia", "Aruba", "Australia"), Currency = c("GBP", "GBP",
"GBP", "GBP", "GBP", "GBP", "GBP", "GBP", "GBP", "GBP", "GBP",
"GBP", "GBP", "GBP", "GBP", "GBP", "GBP", "GBP", "GBP", "GBP",
"GBP"), CoeffqPPP = c(0.184436278, 0.184436278, 0.367527677,
0.184436278, 0.994525717, 0.184436278, 0.184436278, 0.184436278,
0.112411792, 0, 0.112411792, 0.347344672, 0.367527677, 0.367527677,
0.994525717, 0.264750217, 0.994525717, 0.389806873, 0.188019865,
0.994525717, 0.994525717), Step = c(3, 3, 3, 3, 3, 3, 3,
3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3), Coeffq = c(2756.10980649717,
2756.10980649717, 2756.10980649717, 2756.10980649717, 2756.10980649717,
2756.10980649717, 2756.10980649717, 2756.10980649717, 2756.10980649717,
2756.10980649717, 2756.10980649717, 2756.10980649717, 2756.10980649717,
2756.10980649717, 2756.10980649717, 2756.10980649717, 2756.10980649717,
2756.10980649717, 2756.10980649717, 2756.10980649717, 2756.10980649717
), CoeffqYear = c("2017", "2017", "2017", "2017", "2017",
"2017", "2017", "2017", "2017", "2017", "2017", "2017", "2017",
"2017", "2017", "2017", "2017", "2017", "2017", "2017", "2017"
), CoeffqUnit = c("GBP", "GBP", "GBP", "GBP", "GBP", "GBP",
"GBP", "GBP", "GBP", "GBP", "GBP", "GBP", "GBP", "GBP", "GBP",
"GBP", "GBP", "GBP", "GBP", "GBP", "GBP"), Step2iresult = c(1.32904727554592,
1.57109861939866, 1.51662503362256, 1.36459757855418, 1.43822197171544,
1.52718971619107, 1.42584162253612, 1.57235105117809, 1.49249538546973,
1.61196860639412, 1.72684237959508, 1.58018758409756, 1.46113405578585,
1.56484787181204, 1.75672729723484, 1.73477786082112, 1.74783098133106,
1.45534919185534, 1.69904146852532, 1.46098338458917, 1.74351956410071
), iresult_pos = c(3564.46552325877, 4213.64007550875, 4067.54352800449,
3659.81038551155, 3857.2688325682, 4095.8776944954, 3824.06510187511,
4216.9990605352, 4002.82852462449, 4442.76248384841, 4759.36721667692,
4355.17049663636, 4027.04589975837, 4312.8925651774, 4841.73333125022,
4781.23827430327, 4817.21410774609, 4011.10217955023, 4682.744853048,
4026.63063339563, 4805.33136843763), iresult_posPPP = c(675.590128629298,
798.631273618818, 1536.26022396863, 693.661294511865, 3942.19818248036,
776.311208628047, 724.793273270513, 799.267918050159, 462.403789458181,
0, 535.008997612704, 1512.74526765823, 1480.05082471057,
1585.10738563022, 4815.22831278442, 1265.8338706505, 4790.8433144487,
1563.55519789396, 880.449055099529, 4004.58771777195, 4779.02562461803
), iresult_pos_m = c(0.00356446552325877, 0.00421364007550875,
0.00406754352800449, 0.00365981038551155, 0.0038572688325682,
0.0040958776944954, 0.00382406510187511, 0.0042169990605352,
0.00400282852462449, 0.00444276248384841, 0.00475936721667692,
0.00435517049663636, 0.00402704589975837, 0.0043128925651774,
0.00484173333125022, 0.00478123827430327, 0.00481721410774609,
0.00401110217955023, 0.004682744853048, 0.00402663063339563,
0.00480533136843763), ID = c(NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA),
StepName = c("Avoided cost of Dementia", "Avoided cost of Dementia",
"Avoided cost of Dementia", "Avoided cost of Dementia", "Avoided cost of Dementia",
"Avoided cost of Dementia", "Avoided cost of Dementia", "Avoided cost of Dementia",
"Avoided cost of Dementia", "Avoided cost of Dementia", "Avoided cost of Dementia",
"Avoided cost of Dementia", "Avoided cost of Dementia", "Avoided cost of Dementia",
"Avoided cost of Dementia", "Avoided cost of Dementia", "Avoided cost of Dementia",
"Avoided cost of Dementia", "Avoided cost of Dementia", "Avoided cost of Dementia",
"Avoided cost of Dementia"), ImpactID = c(10L, 10L, 10L,
10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L,
10L, 10L, 10L, 10L, 10L, 10L), Allocation = c(1, 1, 1, 1,
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1), Polarity = c("Positive",
"Positive", "Positive", "Positive", "Positive", "Positive",
"Positive", "Positive", "Positive", "Positive", "Positive",
"Positive", "Positive", "Positive", "Positive", "Positive",
"Positive", "Positive", "Positive", "Positive", "Positive"
), Waterfall = c("Yes", "Yes", "Yes", "Yes", "Yes", "Yes",
"Yes", "Yes", "Yes", "Yes", "Yes", "Yes", "Yes", "Yes", "Yes",
"Yes", "Yes", "Yes", "Yes", "Yes", "Yes"), Int_Ext = c("External",
"External", "External", "External", "External", "External",
"External", "External", "External", "External", "External",
"External", "External", "External", "External", "External",
"External", "External", "External", "External", "External"
), ImpactCode = c("GDF", "GDF", "GDF", "GDF", "GDF", "GDF",
"GDF", "GDF", "GDF", "GDF", "GDF", "GDF", "GDF", "GDF", "GDF",
"GDF", "GDF", "GDF", "GDF", "GDF", "GDF"), ImpactName = c("Government // Direct Financial",
"Government // Direct Financial", "Government // Direct Financial",
"Government // Direct Financial", "Government // Direct Financial",
"Government // Direct Financial", "Government // Direct Financial",
"Government // Direct Financial", "Government // Direct Financial",
"Government // Direct Financial", "Government // Direct Financial",
"Government // Direct Financial", "Government // Direct Financial",
"Government // Direct Financial", "Government // Direct Financial",
"Government // Direct Financial", "Government // Direct Financial",
"Government // Direct Financial", "Government // Direct Financial",
"Government // Direct Financial", "Government // Direct Financial"
), Name = c("Gym and Leisure Centres", "Gym and Leisure Centres",
"Gym and Leisure Centres", "Gym and Leisure Centres", "Gym and Leisure Centres",
"Gym and Leisure Centres", "Gym and Leisure Centres", "Gym and Leisure Centres",
"Gym and Leisure Centres", "Gym and Leisure Centres", "Gym and Leisure Centres",
"Gym and Leisure Centres", "Gym and Leisure Centres", "Gym and Leisure Centres",
"Gym and Leisure Centres", "Gym and Leisure Centres", "Gym and Leisure Centres",
"Gym and Leisure Centres", "Gym and Leisure Centres", "Gym and Leisure Centres",
"Gym and Leisure Centres"), Capital = c("Manufactured", "Manufactured",
"Manufactured", "Manufactured", "Manufactured", "Manufactured",
"Manufactured", "Manufactured", "Manufactured", "Manufactured",
"Manufactured", "Manufactured", "Manufactured", "Manufactured",
"Manufactured", "Manufactured", "Manufactured", "Manufactured",
"Manufactured", "Manufactured", "Manufactured"), Flow = c("TBC",
"TBC", "TBC", "TBC", "TBC", "TBC", "TBC", "TBC", "TBC", "TBC",
"TBC", "TBC", "TBC", "TBC", "TBC", "TBC", "TBC", "TBC", "TBC",
"TBC", "TBC"), iresult = c(3564.46552325877, 4213.64007550875,
4067.54352800449, 3659.81038551155, 3857.2688325682, 4095.8776944954,
3824.06510187511, 4216.9990605352, 4002.82852462449, 4442.76248384841,
4759.36721667692, 4355.17049663636, 4027.04589975837, 4312.8925651774,
4841.73333125022, 4781.23827430327, 4817.21410774609, 4011.10217955023,
4682.744853048, 4026.63063339563, 4805.33136843763), iresult_m = c(0.00356446552325877,
0.00421364007550875, 0.00406754352800449, 0.00365981038551155,
0.0038572688325682, 0.0040958776944954, 0.00382406510187511,
0.0042169990605352, 0.00400282852462449, 0.00444276248384841,
0.00475936721667692, 0.00435517049663636, 0.00402704589975837,
0.0043128925651774, 0.00484173333125022, 0.00478123827430327,
0.00481721410774609, 0.00401110217955023, 0.004682744853048,
0.00402663063339563, 0.00480533136843763)), row.names = 1760:1780, class = "data.frame")
这是我目前正在尝试获得的代码要点 运行，目前正在考虑 if 语句方法：
Data %>%
mutate(iresult_pos = ifelse(ISO= 'ALL', (sum of the rows in iresult_posPPP where DataYear, Division, FurtherDetails1 and FutherDetails2 are the same), iresult_posPPP)
有没有一种简洁的方法可以做到这一点，或者我可能遗漏了一个步骤，因为我一直在绞尽脑汁/绕过堆栈溢出线程，想不出一个好的方法来做到这一点。任何帮助将不胜感激！
谢谢！
可能我们需要按总和分组
library(dplyr)
Data %>%
group_by(DataYear, Division, FurtherDetails1, FurtherDetails2) %>%
mutate(iresult_pos =sum(iresult_posPPP))
另一个选项，使用虚拟数据集来展示它是如何工作的：
# create dummy data
data <- data.frame(replicate(10,sample(0:1,1000,rep=TRUE)))
# sum X2, X3, X4, X9 where X1 == 1, store as X11
data <- data %>% mutate(
X11 = rowSums(select_(.,'X2','X3','X4','X9')))